Overview

Brought to you by YData

Dataset statistics

Number of variables39
Number of observations8885
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 MiB
Average record size in memory138.0 B

Variable types

Numeric11
Categorical2
Boolean26

Alerts

estado_civil_CASADO is highly overall correlated with estado_civil_SOLTEROHigh correlation
estado_civil_SOLTERO is highly overall correlated with estado_civil_CASADOHigh correlation
estado_cliente_ACTIVO is highly overall correlated with estado_cliente_PASIVO and 2 other fieldsHigh correlation
estado_cliente_PASIVO is highly overall correlated with estado_cliente_ACTIVO and 2 other fieldsHigh correlation
falta_pago_N is highly overall correlated with estado_cliente_ACTIVO and 3 other fieldsHigh correlation
falta_pago_Y is highly overall correlated with estado_cliente_ACTIVO and 3 other fieldsHigh correlation
gastos_ult_12m is highly overall correlated with operaciones_ult_12mHigh correlation
genero_F is highly overall correlated with genero_MHigh correlation
genero_M is highly overall correlated with genero_FHigh correlation
importe_solicitado is highly overall correlated with pct_ingresoHigh correlation
operaciones_ult_12m is highly overall correlated with gastos_ult_12mHigh correlation
pct_ingreso is highly overall correlated with importe_solicitadoHigh correlation
situacion_vivienda_ALQUILER is highly overall correlated with situacion_vivienda_HIPOTECAHigh correlation
situacion_vivienda_HIPOTECA is highly overall correlated with situacion_vivienda_ALQUILERHigh correlation
tasa_interes is highly overall correlated with falta_pago_N and 1 other fieldsHigh correlation
situacion_vivienda_OTROS is highly imbalanced (96.3%) Imbalance
situacion_vivienda_PROPIA is highly imbalanced (63.8%) Imbalance
objetivo_credito_MEJORAS_HOGAR is highly imbalanced (57.6%) Imbalance
estado_civil_DESCONOCIDO is highly imbalanced (62.2%) Imbalance
estado_civil_DIVORCIADO is highly imbalanced (61.7%) Imbalance
nivel_educativo_POSGRADO_COMPLETO is highly imbalanced (72.9%) Imbalance
nivel_educativo_POSGRADO_INCOMPLETO is highly imbalanced (70.6%) Imbalance
antiguedad_empleado has 1276 (14.4%) zeros Zeros
personas_a_cargo has 787 (8.9%) zeros Zeros

Reproduction

Analysis started2025-07-23 05:26:10.174820
Analysis finished2025-07-23 05:26:18.228831
Duration8.05 seconds
Software versionydata-profiling vv4.13.0
Download configurationconfig.json

Variables

edad
Real number (ℝ)

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.540011
Minimum20
Maximum26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size138.8 KiB
2025-07-23T00:26:18.253784image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile21
Q122
median23
Q325
95-th percentile26
Maximum26
Range6
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.5115131
Coefficient of variation (CV)0.064210383
Kurtosis-1.0415922
Mean23.540011
Median Absolute Deviation (MAD)1
Skewness0.10762074
Sum209153
Variance2.284672
MonotonicityNot monotonic
2025-07-23T00:26:18.289797image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
22 1937
21.8%
23 1925
21.7%
24 1697
19.1%
25 1444
16.3%
26 1184
13.3%
21 692
 
7.8%
20 6
 
0.1%
ValueCountFrequency (%)
20 6
 
0.1%
21 692
 
7.8%
22 1937
21.8%
23 1925
21.7%
24 1697
19.1%
25 1444
16.3%
26 1184
13.3%
ValueCountFrequency (%)
26 1184
13.3%
25 1444
16.3%
24 1697
19.1%
23 1925
21.7%
22 1937
21.8%
21 692
 
7.8%
20 6
 
0.1%

importe_solicitado
Real number (ℝ)

High correlation 

Distinct486
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8178.3371
Minimum500
Maximum35000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size138.8 KiB
2025-07-23T00:26:18.334465image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum500
5-th percentile2000
Q14500
median6500
Q310000
95-th percentile20000
Maximum35000
Range34500
Interquartile range (IQR)5500

Descriptive statistics

Standard deviation5766.519
Coefficient of variation (CV)0.70509676
Kurtosis2.3530343
Mean8178.3371
Median Absolute Deviation (MAD)2500
Skewness1.5276693
Sum72664525
Variance33252741
MonotonicityNot monotonic
2025-07-23T00:26:18.387374image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5000 693
 
7.8%
6000 641
 
7.2%
8000 499
 
5.6%
7000 390
 
4.4%
4000 386
 
4.3%
10000 333
 
3.7%
3000 325
 
3.7%
20000 253
 
2.8%
12000 228
 
2.6%
9000 221
 
2.5%
Other values (476) 4916
55.3%
ValueCountFrequency (%)
500 3
 
< 0.1%
700 1
 
< 0.1%
750 1
 
< 0.1%
800 1
 
< 0.1%
900 1
 
< 0.1%
1000 122
1.4%
1050 1
 
< 0.1%
1100 1
 
< 0.1%
1150 1
 
< 0.1%
1200 60
0.7%
ValueCountFrequency (%)
35000 20
0.2%
34800 1
 
< 0.1%
34000 1
 
< 0.1%
33950 1
 
< 0.1%
33000 1
 
< 0.1%
32500 1
 
< 0.1%
32000 1
 
< 0.1%
31300 1
 
< 0.1%
31050 1
 
< 0.1%
30000 19
0.2%

duracion_credito
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size138.8 KiB
2
2996 
3
2945 
4
2944 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters8885
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row2
3rd row2
4th row4
5th row2

Common Values

ValueCountFrequency (%)
2 2996
33.7%
3 2945
33.1%
4 2944
33.1%

Length

2025-07-23T00:26:18.431417image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-07-23T00:26:18.457864image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
2 2996
33.7%
3 2945
33.1%
4 2944
33.1%

Most occurring characters

ValueCountFrequency (%)
2 2996
33.7%
3 2945
33.1%
4 2944
33.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8885
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 2996
33.7%
3 2945
33.1%
4 2944
33.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8885
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 2996
33.7%
3 2945
33.1%
4 2944
33.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8885
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 2996
33.7%
3 2945
33.1%
4 2944
33.1%

antiguedad_empleado
Real number (ℝ)

Zeros 

Distinct13
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.9320203
Minimum0
Maximum123
Zeros1276
Zeros (%)14.4%
Negative0
Negative (%)0.0%
Memory size138.8 KiB
2025-07-23T00:26:18.489581image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median4
Q36
95-th percentile9
Maximum123
Range123
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.3581927
Coefficient of variation (CV)0.85406293
Kurtosis354.08969
Mean3.9320203
Median Absolute Deviation (MAD)2
Skewness10.216099
Sum34936
Variance11.277458
MonotonicityNot monotonic
2025-07-23T00:26:18.525538image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 1276
14.4%
2 1158
13.0%
3 1038
11.7%
5 967
10.9%
6 921
10.4%
1 910
10.2%
4 771
8.7%
7 706
7.9%
8 526
5.9%
9 368
 
4.1%
Other values (3) 244
 
2.7%
ValueCountFrequency (%)
0 1276
14.4%
1 910
10.2%
2 1158
13.0%
3 1038
11.7%
4 771
8.7%
5 967
10.9%
6 921
10.4%
7 706
7.9%
8 526
5.9%
9 368
 
4.1%
ValueCountFrequency (%)
123 2
 
< 0.1%
11 23
 
0.3%
10 219
 
2.5%
9 368
 
4.1%
8 526
5.9%
7 706
7.9%
6 921
10.4%
5 967
10.9%
4 771
8.7%
3 1038
11.7%

ingresos
Real number (ℝ)

Distinct1620
Distinct (%)18.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50928.148
Minimum9600
Maximum500000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size138.8 KiB
2025-07-23T00:26:18.577173image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum9600
5-th percentile21000
Q134000
median47000
Q360000
95-th percentile97000
Maximum500000
Range490400
Interquartile range (IQR)26000

Descriptive statistics

Standard deviation28844.58
Coefficient of variation (CV)0.56637795
Kurtosis21.042824
Mean50928.148
Median Absolute Deviation (MAD)13000
Skewness3.3470595
Sum4.524966 × 108
Variance8.3200981 × 108
MonotonicityNot monotonic
2025-07-23T00:26:18.630728image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
60000 386
 
4.3%
30000 313
 
3.5%
50000 304
 
3.4%
40000 242
 
2.7%
45000 217
 
2.4%
55000 201
 
2.3%
65000 197
 
2.2%
48000 194
 
2.2%
36000 185
 
2.1%
42000 176
 
2.0%
Other values (1610) 6470
72.8%
ValueCountFrequency (%)
9600 3
 
< 0.1%
9840 1
 
< 0.1%
9900 1
 
< 0.1%
9960 1
 
< 0.1%
10000 9
0.1%
10560 1
 
< 0.1%
10668 1
 
< 0.1%
10800 3
 
< 0.1%
10980 1
 
< 0.1%
11000 3
 
< 0.1%
ValueCountFrequency (%)
500000 1
 
< 0.1%
306000 1
 
< 0.1%
300000 6
0.1%
287000 1
 
< 0.1%
280000 1
 
< 0.1%
277104 1
 
< 0.1%
275000 1
 
< 0.1%
260000 1
 
< 0.1%
259000 1
 
< 0.1%
255000 1
 
< 0.1%

pct_ingreso
Real number (ℝ)

High correlation 

Distinct69
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.17534271
Minimum0.01
Maximum0.77
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size138.8 KiB
2025-07-23T00:26:18.680907image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile0.04
Q10.09
median0.15
Q30.23
95-th percentile0.39
Maximum0.77
Range0.76
Interquartile range (IQR)0.14

Descriptive statistics

Standard deviation0.10809246
Coefficient of variation (CV)0.61646396
Kurtosis1.1343138
Mean0.17534271
Median Absolute Deviation (MAD)0.07
Skewness1.0618008
Sum1557.92
Variance0.01168398
MonotonicityNot monotonic
2025-07-23T00:26:18.733397image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.1 464
 
5.2%
0.13 406
 
4.6%
0.09 391
 
4.4%
0.11 387
 
4.4%
0.08 386
 
4.3%
0.15 380
 
4.3%
0.12 352
 
4.0%
0.14 348
 
3.9%
0.07 346
 
3.9%
0.17 335
 
3.8%
Other values (59) 5090
57.3%
ValueCountFrequency (%)
0.01 17
 
0.2%
0.02 81
 
0.9%
0.03 198
2.2%
0.04 249
2.8%
0.05 262
2.9%
0.06 304
3.4%
0.07 346
3.9%
0.08 386
4.3%
0.09 391
4.4%
0.1 464
5.2%
ValueCountFrequency (%)
0.77 1
 
< 0.1%
0.71 1
 
< 0.1%
0.69 2
< 0.1%
0.68 1
 
< 0.1%
0.67 1
 
< 0.1%
0.65 2
< 0.1%
0.64 3
< 0.1%
0.63 3
< 0.1%
0.61 2
< 0.1%
0.6 2
< 0.1%

tasa_interes
Real number (ℝ)

High correlation 

Distinct306
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.019078
Minimum5.42
Maximum22.11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size138.8 KiB
2025-07-23T00:26:18.782334image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum5.42
5-th percentile6.03
Q17.9
median10.99
Q313.47
95-th percentile16.29
Maximum22.11
Range16.69
Interquartile range (IQR)5.57

Descriptive statistics

Standard deviation3.1950886
Coefficient of variation (CV)0.2899597
Kurtosis-0.70377572
Mean11.019078
Median Absolute Deviation (MAD)2.5
Skewness0.18486503
Sum97904.51
Variance10.208591
MonotonicityNot monotonic
2025-07-23T00:26:18.834025image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10.99 252
 
2.8%
7.51 227
 
2.6%
7.9 189
 
2.1%
7.49 187
 
2.1%
7.88 173
 
1.9%
5.42 171
 
1.9%
9.99 148
 
1.7%
11.49 143
 
1.6%
11.71 132
 
1.5%
13.49 132
 
1.5%
Other values (296) 7131
80.3%
ValueCountFrequency (%)
5.42 171
1.9%
5.79 106
1.2%
5.99 112
1.3%
6 6
 
0.1%
6.03 121
1.4%
6.17 59
 
0.7%
6.39 14
 
0.2%
6.54 72
0.8%
6.62 116
1.3%
6.76 61
 
0.7%
ValueCountFrequency (%)
22.11 1
< 0.1%
21.74 2
< 0.1%
21.36 1
< 0.1%
21.27 1
< 0.1%
21.21 1
< 0.1%
20.89 2
< 0.1%
20.62 1
< 0.1%
20.3 2
< 0.1%
20.25 1
< 0.1%
20.2 1
< 0.1%

estado_credito
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size138.8 KiB
0
6715 
1
2170 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters8885
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row0
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
0 6715
75.6%
1 2170
 
24.4%

Length

2025-07-23T00:26:18.880230image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-07-23T00:26:19.066957image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 6715
75.6%
1 2170
 
24.4%

Most occurring characters

ValueCountFrequency (%)
0 6715
75.6%
1 2170
 
24.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8885
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 6715
75.6%
1 2170
 
24.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8885
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 6715
75.6%
1 2170
 
24.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8885
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 6715
75.6%
1 2170
 
24.4%

antiguedad_cliente
Real number (ℝ)

Distinct44
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.886888
Minimum13
Maximum56
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size138.8 KiB
2025-07-23T00:26:19.100362image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum13
5-th percentile22
Q131
median36
Q340
95-th percentile50
Maximum56
Range43
Interquartile range (IQR)9

Descriptive statistics

Standard deviation7.994337
Coefficient of variation (CV)0.22276484
Kurtosis0.41257386
Mean35.886888
Median Absolute Deviation (MAD)4
Skewness-0.10222955
Sum318855
Variance63.909424
MonotonicityNot monotonic
2025-07-23T00:26:19.146945image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
36 2127
23.9%
37 316
 
3.6%
34 313
 
3.5%
38 305
 
3.4%
40 304
 
3.4%
39 302
 
3.4%
31 296
 
3.3%
33 278
 
3.1%
35 272
 
3.1%
30 262
 
2.9%
Other values (34) 4110
46.3%
ValueCountFrequency (%)
13 63
0.7%
14 15
 
0.2%
15 29
 
0.3%
16 28
 
0.3%
17 35
 
0.4%
18 49
0.6%
19 55
0.6%
20 68
0.8%
21 75
0.8%
22 93
1.0%
ValueCountFrequency (%)
56 94
1.1%
55 36
 
0.4%
54 47
 
0.5%
53 65
0.7%
52 56
 
0.6%
51 70
0.8%
50 83
0.9%
49 127
1.4%
48 136
1.5%
47 145
1.6%

gastos_ult_12m
Real number (ℝ)

High correlation 

Distinct4718
Distinct (%)53.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4428.9916
Minimum510
Maximum18484
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size138.8 KiB
2025-07-23T00:26:19.195998image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum510
5-th percentile1289
Q12164
median3913
Q34748
95-th percentile14230
Maximum18484
Range17974
Interquartile range (IQR)2584

Descriptive statistics

Standard deviation3426.2826
Coefficient of variation (CV)0.77360332
Kurtosis3.8093547
Mean4428.9916
Median Absolute Deviation (MAD)1313
Skewness2.0305055
Sum39351590
Variance11739412
MonotonicityNot monotonic
2025-07-23T00:26:19.250478image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4253 10
 
0.1%
4509 10
 
0.1%
4518 9
 
0.1%
2229 9
 
0.1%
4037 8
 
0.1%
4220 8
 
0.1%
4077 8
 
0.1%
4498 8
 
0.1%
4348 8
 
0.1%
4313 8
 
0.1%
Other values (4708) 8799
99.0%
ValueCountFrequency (%)
510 1
< 0.1%
530 1
< 0.1%
563 1
< 0.1%
569 1
< 0.1%
594 1
< 0.1%
596 1
< 0.1%
597 1
< 0.1%
615 1
< 0.1%
643 1
< 0.1%
644 1
< 0.1%
ValueCountFrequency (%)
18484 1
< 0.1%
17995 1
< 0.1%
17744 1
< 0.1%
17634 1
< 0.1%
17628 1
< 0.1%
17498 1
< 0.1%
17437 1
< 0.1%
17390 1
< 0.1%
17350 1
< 0.1%
17258 1
< 0.1%

limite_credito_tc
Real number (ℝ)

Distinct5672
Distinct (%)63.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8608.2363
Minimum1438.3
Maximum34516
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size138.8 KiB
2025-07-23T00:26:19.310822image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1438.3
5-th percentile1438.3
Q12548
median4543
Q311059
95-th percentile34516
Maximum34516
Range33077.7
Interquartile range (IQR)8511

Descriptive statistics

Standard deviation9065.5877
Coefficient of variation (CV)1.0531295
Kurtosis1.8426853
Mean8608.2363
Median Absolute Deviation (MAD)2597
Skewness1.6726733
Sum76484180
Variance82184880
MonotonicityNot monotonic
2025-07-23T00:26:19.365761image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1438.3 453
 
5.1%
34516 449
 
5.1%
15987 18
 
0.2%
9959 14
 
0.2%
23981 11
 
0.1%
6224 11
 
0.1%
3735 10
 
0.1%
2490 10
 
0.1%
7469 9
 
0.1%
14938 7
 
0.1%
Other values (5662) 7893
88.8%
ValueCountFrequency (%)
1438.3 453
5.1%
1439 2
 
< 0.1%
1440 1
 
< 0.1%
1441 2
 
< 0.1%
1442 1
 
< 0.1%
1443 3
 
< 0.1%
1446 1
 
< 0.1%
1449 2
 
< 0.1%
1451 2
 
< 0.1%
1452 2
 
< 0.1%
ValueCountFrequency (%)
34516 449
5.1%
34496 1
 
< 0.1%
34458 1
 
< 0.1%
34427 1
 
< 0.1%
34198 1
 
< 0.1%
34173 1
 
< 0.1%
34162 1
 
< 0.1%
34140 1
 
< 0.1%
34058 1
 
< 0.1%
33996 1
 
< 0.1%

operaciones_ult_12m
Real number (ℝ)

High correlation 

Distinct125
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean64.99955
Minimum10
Maximum139
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size138.8 KiB
2025-07-23T00:26:19.424221image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile28
Q145
median67
Q381
95-th percentile106
Maximum139
Range129
Interquartile range (IQR)36

Descriptive statistics

Standard deviation23.520686
Coefficient of variation (CV)0.36185921
Kurtosis-0.35709879
Mean64.99955
Median Absolute Deviation (MAD)17
Skewness0.15342237
Sum577521
Variance553.22265
MonotonicityNot monotonic
2025-07-23T00:26:19.475992image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
69 185
 
2.1%
81 181
 
2.0%
71 180
 
2.0%
75 179
 
2.0%
76 173
 
1.9%
78 173
 
1.9%
82 172
 
1.9%
77 172
 
1.9%
70 166
 
1.9%
67 163
 
1.8%
Other values (115) 7141
80.4%
ValueCountFrequency (%)
10 3
 
< 0.1%
11 2
 
< 0.1%
12 4
 
< 0.1%
13 5
 
0.1%
14 8
 
0.1%
15 12
0.1%
16 12
0.1%
17 12
0.1%
18 21
0.2%
19 10
0.1%
ValueCountFrequency (%)
139 1
 
< 0.1%
138 1
 
< 0.1%
134 1
 
< 0.1%
131 6
0.1%
130 5
0.1%
129 5
0.1%
128 9
0.1%
127 10
0.1%
126 10
0.1%
125 12
0.1%

personas_a_cargo
Real number (ℝ)

Zeros 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.352054
Minimum0
Maximum5
Zeros787
Zeros (%)8.9%
Negative0
Negative (%)0.0%
Memory size138.8 KiB
2025-07-23T00:26:19.521936image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile4
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.3006412
Coefficient of variation (CV)0.55298102
Kurtosis-0.68916511
Mean2.352054
Median Absolute Deviation (MAD)1
Skewness-0.022336426
Sum20898
Variance1.6916676
MonotonicityNot monotonic
2025-07-23T00:26:19.555900image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
3 2389
26.9%
2 2321
26.1%
1 1613
18.2%
4 1399
15.7%
0 787
 
8.9%
5 376
 
4.2%
ValueCountFrequency (%)
0 787
 
8.9%
1 1613
18.2%
2 2321
26.1%
3 2389
26.9%
4 1399
15.7%
5 376
 
4.2%
ValueCountFrequency (%)
5 376
 
4.2%
4 1399
15.7%
3 2389
26.9%
2 2321
26.1%
1 1613
18.2%
0 787
 
8.9%

situacion_vivienda_ALQUILER
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.1 KiB
True
5432 
False
3453 
ValueCountFrequency (%)
True 5432
61.1%
False 3453
38.9%
2025-07-23T00:26:19.582521image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

situacion_vivienda_HIPOTECA
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.1 KiB
False
6080 
True
2805 
ValueCountFrequency (%)
False 6080
68.4%
True 2805
31.6%
2025-07-23T00:26:19.605193image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

situacion_vivienda_OTROS
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.1 KiB
False
8850 
True
 
35
ValueCountFrequency (%)
False 8850
99.6%
True 35
 
0.4%
2025-07-23T00:26:19.625501image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

situacion_vivienda_PROPIA
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.1 KiB
False
8272 
True
 
613
ValueCountFrequency (%)
False 8272
93.1%
True 613
 
6.9%
2025-07-23T00:26:19.643860image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.1 KiB
False
6820 
True
2065 
ValueCountFrequency (%)
False 6820
76.8%
True 2065
 
23.2%
2025-07-23T00:26:19.661361image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.1 KiB
False
7366 
True
1519 
ValueCountFrequency (%)
False 7366
82.9%
True 1519
 
17.1%
2025-07-23T00:26:19.682076image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.1 KiB
False
8117 
True
 
768
ValueCountFrequency (%)
False 8117
91.4%
True 768
 
8.6%
2025-07-23T00:26:19.701850image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.1 KiB
False
7423 
True
1462 
ValueCountFrequency (%)
False 7423
83.5%
True 1462
 
16.5%
2025-07-23T00:26:19.722332image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.1 KiB
False
7428 
True
1457 
ValueCountFrequency (%)
False 7428
83.6%
True 1457
 
16.4%
2025-07-23T00:26:19.740882image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.1 KiB
False
7271 
True
1614 
ValueCountFrequency (%)
False 7271
81.8%
True 1614
 
18.2%
2025-07-23T00:26:19.761284image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

falta_pago_N
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.1 KiB
True
7320 
False
1565 
ValueCountFrequency (%)
True 7320
82.4%
False 1565
 
17.6%
2025-07-23T00:26:19.780421image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

falta_pago_Y
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.1 KiB
False
7320 
True
1565 
ValueCountFrequency (%)
False 7320
82.4%
True 1565
 
17.6%
2025-07-23T00:26:19.801301image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

estado_civil_CASADO
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.1 KiB
False
4783 
True
4102 
ValueCountFrequency (%)
False 4783
53.8%
True 4102
46.2%
2025-07-23T00:26:19.822622image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

estado_civil_DESCONOCIDO
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.1 KiB
False
8233 
True
 
652
ValueCountFrequency (%)
False 8233
92.7%
True 652
 
7.3%
2025-07-23T00:26:19.844926image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

estado_civil_DIVORCIADO
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.1 KiB
False
8221 
True
 
664
ValueCountFrequency (%)
False 8221
92.5%
True 664
 
7.5%
2025-07-23T00:26:19.862810image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

estado_civil_SOLTERO
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.1 KiB
False
5418 
True
3467 
ValueCountFrequency (%)
False 5418
61.0%
True 3467
39.0%
2025-07-23T00:26:19.881465image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

estado_cliente_ACTIVO
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.1 KiB
True
7440 
False
1445 
ValueCountFrequency (%)
True 7440
83.7%
False 1445
 
16.3%
2025-07-23T00:26:19.904345image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

estado_cliente_PASIVO
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.1 KiB
False
7440 
True
1445 
ValueCountFrequency (%)
False 7440
83.7%
True 1445
 
16.3%
2025-07-23T00:26:19.926051image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

genero_F
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.1 KiB
True
4720 
False
4165 
ValueCountFrequency (%)
True 4720
53.1%
False 4165
46.9%
2025-07-23T00:26:19.944530image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

genero_M
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.1 KiB
False
4720 
True
4165 
ValueCountFrequency (%)
False 4720
53.1%
True 4165
46.9%
2025-07-23T00:26:19.965125image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.1 KiB
False
7571 
True
1314 
ValueCountFrequency (%)
False 7571
85.2%
True 1314
 
14.8%
2025-07-23T00:26:19.985141image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.1 KiB
False
8472 
True
 
413
ValueCountFrequency (%)
False 8472
95.4%
True 413
 
4.6%
2025-07-23T00:26:20.003528image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.1 KiB
False
8424 
True
 
461
ValueCountFrequency (%)
False 8424
94.8%
True 461
 
5.2%
2025-07-23T00:26:20.022879image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.1 KiB
False
7122 
True
1763 
ValueCountFrequency (%)
False 7122
80.2%
True 1763
 
19.8%
2025-07-23T00:26:20.041722image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.1 KiB
False
6143 
True
2742 
ValueCountFrequency (%)
False 6143
69.1%
True 2742
30.9%
2025-07-23T00:26:20.063141image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.1 KiB
False
6693 
True
2192 
ValueCountFrequency (%)
False 6693
75.3%
True 2192
 
24.7%
2025-07-23T00:26:20.083173image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Interactions

2025-07-23T00:26:17.450849image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:12.057003image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:12.562497image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:13.249580image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:13.738983image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:14.223738image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:14.745055image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:15.263061image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:15.741747image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:16.407236image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:16.957367image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:17.495594image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:12.099244image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:12.766492image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:13.295779image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:13.781390image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:14.269998image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:14.791100image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:15.304394image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:15.788681image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:16.452645image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:16.999876image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:17.546006image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:12.146706image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:12.811523image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:13.342731image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:13.825379image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:14.315795image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:14.841055image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:15.349313image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:15.840499image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:16.504702image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:17.047967image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:17.594037image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:12.194068image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:12.858068image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:13.383331image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:13.869881image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:14.363999image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:14.886711image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:15.392571image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:15.885570image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:16.548963image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:17.091172image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:17.636354image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:12.240655image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:12.903697image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:13.427547image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:13.912159image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:14.410630image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:14.933061image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:15.437618image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:15.930239image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:16.593787image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:17.134727image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:17.679092image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:12.292230image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:12.953782image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:13.473781image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:13.957326image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:14.457591image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:14.979285image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:15.482985image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:15.977385image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:16.643055image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:17.181886image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:17.724367image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:12.336878image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:13.000489image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:13.520617image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:14.000063image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:14.508215image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:15.026735image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:15.527193image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:16.026010image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:16.686842image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:17.227797image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:17.763455image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:12.377413image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:13.044557image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:13.560486image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:14.039563image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:14.554810image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:15.071002image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:15.565381image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:16.225019image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:16.763609image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:17.269215image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:17.805979image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:12.426217image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:13.092800image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:13.607446image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:14.085010image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:14.604869image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:15.119123image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:15.609085image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:16.269185image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:16.810959image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:17.312691image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:17.849793image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:12.474086image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:13.141747image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:13.654126image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:14.130837image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:14.653883image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:15.166898image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:15.656104image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:16.313062image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:16.861554image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:17.360611image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:17.892205image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:12.520442image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:13.189222image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:13.697087image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:14.178513image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:14.700605image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:15.216602image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:15.698464image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:16.359296image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:16.911280image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-07-23T00:26:17.403091image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-07-23T00:26:20.134893image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
antiguedad_clienteantiguedad_empleadoduracion_creditoedadestado_civil_CASADOestado_civil_DESCONOCIDOestado_civil_DIVORCIADOestado_civil_SOLTEROestado_cliente_ACTIVOestado_cliente_PASIVOestado_creditofalta_pago_Nfalta_pago_Ygastos_ult_12mgenero_Fgenero_Mimporte_solicitadoingresoslimite_credito_tcnivel_educativo_DESCONOCIDOnivel_educativo_POSGRADO_COMPLETOnivel_educativo_POSGRADO_INCOMPLETOnivel_educativo_SECUNDARIO_COMPLETOnivel_educativo_UNIVERSITARIO_COMPLETOnivel_educativo_UNIVERSITARIO_INCOMPLETOobjetivo_credito_EDUCACIÓNobjetivo_credito_INVERSIONESobjetivo_credito_MEJORAS_HOGARobjetivo_credito_PAGO_DEUDASobjetivo_credito_PERSONALobjetivo_credito_SALUDoperaciones_ult_12mpct_ingresopersonas_a_cargosituacion_vivienda_ALQUILERsituacion_vivienda_HIPOTECAsituacion_vivienda_OTROSsituacion_vivienda_PROPIAtasa_interes
antiguedad_cliente1.000-0.0010.000-0.0010.0490.0360.0400.0510.0320.0320.0260.0500.050-0.0240.0190.0190.0380.0130.0090.0000.0220.0290.0000.0240.0100.0000.0000.0130.0320.0160.000-0.0360.034-0.1150.0300.0330.0000.0000.009
antiguedad_empleado-0.0011.0000.0000.1090.0000.0000.0000.0000.0000.0000.0000.0000.0000.0630.0000.0000.1210.188-0.0040.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.057-0.002-0.0020.0000.0000.0000.000-0.065
duracion_credito0.0000.0001.0000.0060.0000.0000.0150.0000.0050.0050.0000.0000.0000.0000.0000.0000.0000.0030.0080.0080.0160.0000.0000.0320.0250.0000.0010.0090.0130.0220.0220.0000.0000.0160.0060.0110.0000.0000.017
edad-0.0010.1090.0061.0000.0170.0000.0150.0070.0160.0160.0400.0000.0000.0090.0000.0000.0780.1550.0110.0000.0000.0130.0000.0000.0000.1590.0100.2040.0050.0110.0390.008-0.0370.0020.0000.0230.0230.0250.005
estado_civil_CASADO0.0490.0000.0000.0171.0000.2600.2630.7410.0240.0240.0430.0000.0000.1750.0000.0000.0910.0220.0640.0050.0000.0000.0000.0130.0140.0190.0140.0100.0000.0000.0000.1720.0560.0220.0170.0140.0080.0000.000
estado_civil_DESCONOCIDO0.0360.0000.0000.0000.2601.0000.0780.2240.0000.0000.0190.0000.0000.0560.0110.0110.0420.0330.0170.0000.0000.0070.0000.0000.0000.0060.0000.0000.0000.0000.0000.0300.0000.0390.0130.0040.0000.0000.011
estado_civil_DIVORCIADO0.0400.0000.0150.0150.2630.0781.0000.2270.0000.0000.0000.0000.0000.0390.0000.0000.0000.0000.0210.0160.0000.0000.0090.0000.0340.0000.0190.0000.0000.0000.0000.0390.0120.0300.0000.0000.0000.0000.026
estado_civil_SOLTERO0.0510.0000.0000.0070.7410.2240.2271.0000.0170.0170.0320.0000.0000.1420.0130.0130.0690.0060.0330.0200.0000.0000.0000.0050.0000.0060.0000.0150.0000.0000.0060.1410.0380.0380.0220.0170.0000.0000.000
estado_cliente_ACTIVO0.0320.0000.0050.0160.0240.0000.0000.0171.0001.0000.1170.5510.5510.3280.0310.0310.1070.0190.0340.0070.0310.0000.0060.0000.0000.0150.0000.0210.0000.0000.0000.4570.0400.0190.0520.0530.0000.0000.319
estado_cliente_PASIVO0.0320.0000.0050.0160.0240.0000.0000.0171.0001.0000.1170.5510.5510.3280.0310.0310.1070.0190.0340.0070.0310.0000.0060.0000.0000.0150.0000.0210.0000.0000.0000.4570.0400.0190.0520.0530.0000.0000.319
estado_credito0.0260.0000.0000.0400.0430.0190.0000.0320.1170.1171.0000.1920.1920.2320.0260.0260.2110.1170.0000.0000.0060.0090.0080.0000.0000.0950.0630.1110.0620.0140.0420.2400.4040.0000.2070.1650.0230.1010.384
falta_pago_N0.0500.0000.0000.0000.0000.0000.0000.0000.5510.5510.1921.0001.0000.2610.0000.0000.0560.0000.0290.0000.0000.0000.0070.0040.0000.0140.0170.0490.0030.0000.0000.3240.0430.0160.0720.0740.0120.0000.561
falta_pago_Y0.0500.0000.0000.0000.0000.0000.0000.0000.5510.5510.1921.0001.0000.2610.0000.0000.0560.0000.0290.0000.0000.0000.0070.0040.0000.0140.0170.0490.0030.0000.0000.3240.0430.0160.0720.0740.0120.0000.561
gastos_ult_12m-0.0240.0630.0000.0090.1750.0560.0390.1420.3280.3280.2320.2610.2611.0000.2470.2470.0340.1560.0270.0210.0120.0000.0430.0000.0000.0120.0130.0000.0000.0000.0000.879-0.0720.0590.1520.1810.0000.037-0.187
genero_F0.0190.0000.0000.0000.0000.0110.0000.0130.0310.0310.0260.0000.0000.2471.0001.0000.1710.1130.4420.0000.0070.0000.0130.0000.0000.0090.0000.0000.0000.0000.0070.1680.0710.0000.0400.0420.0000.0000.002
genero_M0.0190.0000.0000.0000.0000.0110.0000.0130.0310.0310.0260.0000.0000.2471.0001.0000.1710.1130.4420.0000.0070.0000.0130.0000.0000.0090.0000.0000.0000.0000.0070.1680.0710.0000.0400.0420.0000.0000.002
importe_solicitado0.0380.1210.0000.0780.0910.0420.0000.0690.1070.1070.2110.0560.0560.0340.1710.1711.0000.3500.0390.0270.0050.0000.0000.0200.0000.0000.0180.0320.0000.0000.0450.0010.7400.0310.1900.1690.0120.0560.074
ingresos0.0130.1880.0030.1550.0220.0330.0000.0060.0190.0190.1170.0000.0000.1560.1130.1130.3501.0000.0370.0150.0000.0000.0250.0000.0140.0000.0210.0580.0440.0200.0340.129-0.2930.0200.1560.1200.0000.086-0.027
limite_credito_tc0.009-0.0040.0080.0110.0640.0170.0210.0330.0340.0340.0000.0290.0290.0270.4420.4420.0390.0371.0000.0000.0070.0000.0000.0000.0170.0210.0000.0000.0000.0060.0000.0300.0210.0490.0000.0220.0000.0100.003
nivel_educativo_DESCONOCIDO0.0000.0000.0080.0000.0050.0000.0160.0200.0070.0070.0000.0000.0000.0210.0000.0000.0270.0150.0001.0000.0910.0960.2070.2780.2380.0000.0000.0230.0190.0000.0000.0000.0000.0290.0100.0000.0000.0140.000
nivel_educativo_POSGRADO_COMPLETO0.0220.0000.0160.0000.0000.0000.0000.0000.0310.0310.0060.0000.0000.0120.0070.0070.0050.0000.0070.0911.0000.0490.1090.1470.1250.0000.0000.0180.0000.0000.0000.0350.0200.0000.0000.0000.0000.0000.012
nivel_educativo_POSGRADO_INCOMPLETO0.0290.0000.0000.0130.0000.0070.0000.0000.0000.0000.0090.0000.0000.0000.0000.0000.0000.0000.0000.0960.0491.0000.1150.1550.1330.0000.0170.0040.0000.0070.0000.0000.0080.0130.0000.0000.0000.0040.000
nivel_educativo_SECUNDARIO_COMPLETO0.0000.0000.0000.0000.0000.0000.0090.0000.0060.0060.0080.0070.0070.0430.0130.0130.0000.0250.0000.2070.1090.1151.0000.3320.2840.0000.0000.0000.0000.0000.0160.0000.0080.0110.0060.0000.0000.0000.010
nivel_educativo_UNIVERSITARIO_COMPLETO0.0240.0000.0320.0000.0130.0000.0000.0050.0000.0000.0000.0040.0040.0000.0000.0000.0200.0000.0000.2780.1470.1550.3321.0000.3820.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0000.0000.0120.000
nivel_educativo_UNIVERSITARIO_INCOMPLETO0.0100.0000.0250.0000.0140.0000.0340.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0140.0170.2380.1250.1330.2840.3821.0000.0140.0000.0060.0000.0000.0060.0000.0000.0150.0030.0030.0000.0000.000
objetivo_credito_EDUCACIÓN0.0000.0000.0000.1590.0190.0060.0000.0060.0150.0150.0950.0140.0140.0120.0090.0090.0000.0000.0210.0000.0000.0000.0000.0000.0141.0000.2490.1680.2440.2430.2590.0000.0000.0000.0000.0000.0000.0000.035
objetivo_credito_INVERSIONES0.0000.0000.0010.0100.0140.0000.0190.0000.0000.0000.0630.0170.0170.0130.0000.0000.0180.0210.0000.0000.0000.0170.0000.0000.0000.2491.0000.1390.2010.2000.2130.0000.0280.0000.0450.0000.0000.0920.030
objetivo_credito_MEJORAS_HOGAR0.0130.0000.0090.2040.0100.0000.0000.0150.0210.0210.1110.0490.0490.0000.0000.0000.0320.0580.0000.0230.0180.0040.0000.0000.0060.1680.1391.0000.1360.1350.1440.0190.0400.0220.0340.0270.0000.0080.047
objetivo_credito_PAGO_DEUDAS0.0320.0000.0130.0050.0000.0000.0000.0000.0000.0000.0620.0030.0030.0000.0000.0000.0000.0440.0000.0190.0000.0000.0000.0000.0000.2440.2010.1361.0000.1960.2080.0110.0000.0130.0430.0000.0000.0920.015
objetivo_credito_PERSONAL0.0160.0000.0220.0110.0000.0000.0000.0000.0000.0000.0140.0000.0000.0000.0000.0000.0000.0200.0060.0000.0000.0070.0000.0000.0000.2430.2000.1350.1961.0000.2080.0270.0000.0350.0160.0200.0000.0000.016
objetivo_credito_SALUD0.0000.0000.0220.0390.0000.0000.0000.0060.0000.0000.0420.0000.0000.0000.0070.0070.0450.0340.0000.0000.0000.0000.0160.0000.0060.2590.2130.1440.2080.2081.0000.0000.0000.0000.0400.0380.0000.0000.027
operaciones_ult_12m-0.0360.0570.0000.0080.1720.0300.0390.1410.4570.4570.2400.3240.3240.8790.1680.1680.0010.1290.0300.0000.0350.0000.0000.0000.0000.0000.0000.0190.0110.0270.0001.000-0.0820.0560.1360.1650.0000.037-0.219
pct_ingreso0.034-0.0020.000-0.0370.0560.0000.0120.0380.0400.0400.4040.0430.043-0.0720.0710.0710.740-0.2930.0210.0000.0200.0080.0080.0000.0000.0000.0280.0400.0000.0000.000-0.0821.0000.0220.0510.0300.0270.0490.092
personas_a_cargo-0.115-0.0020.0160.0020.0220.0390.0300.0380.0190.0190.0000.0160.0160.0590.0000.0000.0310.0200.0490.0290.0000.0130.0110.0000.0150.0000.0000.0220.0130.0350.0000.0560.0221.0000.0000.0000.0000.015-0.010
situacion_vivienda_ALQUILER0.0300.0000.0060.0000.0170.0130.0000.0220.0520.0520.2070.0720.0720.1520.0400.0400.1900.1560.0000.0100.0000.0000.0060.0040.0030.0000.0450.0340.0430.0160.0400.1360.0510.0001.0000.8520.0760.3410.144
situacion_vivienda_HIPOTECA0.0330.0000.0110.0230.0140.0040.0000.0170.0530.0530.1650.0740.0740.1810.0420.0420.1690.1200.0220.0000.0000.0000.0000.0000.0030.0000.0000.0270.0000.0200.0380.1650.0300.0000.8521.0000.0390.1840.149
situacion_vivienda_OTROS0.0000.0000.0000.0230.0080.0000.0000.0000.0000.0000.0230.0120.0120.0000.0000.0000.0120.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0270.0000.0760.0391.0000.0080.028
situacion_vivienda_PROPIA0.0000.0000.0000.0250.0000.0000.0000.0000.0000.0000.1010.0000.0000.0370.0000.0000.0560.0860.0100.0140.0000.0040.0000.0120.0000.0000.0920.0080.0920.0000.0000.0370.0490.0150.3410.1840.0081.0000.000
tasa_interes0.009-0.0650.0170.0050.0000.0110.0260.0000.3190.3190.3840.5610.561-0.1870.0020.0020.074-0.0270.0030.0000.0120.0000.0100.0000.0000.0350.0300.0470.0150.0160.027-0.2190.092-0.0100.1440.1490.0280.0001.000

Missing values

2025-07-23T00:26:17.982027image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-07-23T00:26:18.127199image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

edadimporte_solicitadoduracion_creditoantiguedad_empleadoingresospct_ingresotasa_interesestado_creditoantiguedad_clientegastos_ult_12mlimite_credito_tcoperaciones_ult_12mpersonas_a_cargosituacion_vivienda_ALQUILERsituacion_vivienda_HIPOTECAsituacion_vivienda_OTROSsituacion_vivienda_PROPIAobjetivo_credito_EDUCACIÓNobjetivo_credito_INVERSIONESobjetivo_credito_MEJORAS_HOGARobjetivo_credito_PAGO_DEUDASobjetivo_credito_PERSONALobjetivo_credito_SALUDfalta_pago_Nfalta_pago_Yestado_civil_CASADOestado_civil_DESCONOCIDOestado_civil_DIVORCIADOestado_civil_SOLTEROestado_cliente_ACTIVOestado_cliente_PASIVOgenero_Fgenero_Mnivel_educativo_DESCONOCIDOnivel_educativo_POSGRADO_COMPLETOnivel_educativo_POSGRADO_INCOMPLETOnivel_educativo_SECUNDARIO_COMPLETOnivel_educativo_UNIVERSITARIO_COMPLETOnivel_educativo_UNIVERSITARIO_INCOMPLETO
022350003123.0590000.5916.02136.01088.04010.024.02.0TrueFalseFalseFalseFalseFalseFalseFalseTrueFalseFalseTrueTrueFalseFalseFalseTrueFalseFalseTrueFalseFalseFalseFalseTrueFalse
121100025.096000.1011.14039.01144.012691.042.03.0FalseFalseFalseTrueTrueFalseFalseFalseFalseFalseTrueFalseTrueFalseFalseFalseTrueFalseFalseTrueFalseFalseFalseTrueFalseFalse
2233500024.0655000.5315.23136.01887.03418.020.03.0TrueFalseFalseFalseFalseFalseFalseFalseFalseTrueTrueFalseTrueFalseFalseFalseTrueFalseFalseTrueFalseFalseFalseFalseTrueFalse
3243500048.0544000.5514.27154.01314.09095.026.01.0TrueFalseFalseFalseFalseFalseFalseFalseFalseTrueFalseTrueTrueFalseFalseFalseTrueFalseFalseTrueTrueFalseFalseFalseFalseFalse
421250022.099000.257.14134.01171.03313.020.04.0FalseFalseFalseTrueFalseTrueFalseFalseFalseFalseTrueFalseFalseTrueFalseFalseTrueFalseTrueFalseFalseFalseFalseTrueFalseFalse
5263500038.0771000.4512.42121.0816.04716.028.03.0TrueFalseFalseFalseTrueFalseFalseFalseFalseFalseTrueFalseTrueFalseFalseFalseTrueFalseFalseTrueFalseFalseFalseFalseFalseTrue
6243500045.0789560.4411.11146.01330.034516.031.04.0TrueFalseFalseFalseFalseFalseFalseFalseFalseTrueTrueFalseTrueFalseFalseFalseTrueFalseFalseTrueTrueFalseFalseFalseFalseFalse
7243500028.0830000.428.90127.01538.029081.036.00.0TrueFalseFalseFalseFalseFalseFalseFalseTrueFalseTrueFalseFalseTrueFalseFalseTrueFalseFalseTrueFalseFalseFalseTrueFalseFalse
821160036.0100000.1614.74136.01350.022352.024.03.0FalseFalseFalseTrueFalseTrueFalseFalseFalseFalseTrueFalseFalseFalseFalseTrueTrueFalseFalseTrueFalseFalseFalseFalseFalseTrue
9223500046.0850000.4110.37136.01441.011656.032.02.0TrueFalseFalseFalseFalseTrueFalseFalseFalseFalseTrueFalseFalseFalseFalseTrueTrueFalseFalseTrueFalseFalseFalseFalseTrueFalse
edadimporte_solicitadoduracion_creditoantiguedad_empleadoingresospct_ingresotasa_interesestado_creditoantiguedad_clientegastos_ult_12mlimite_credito_tcoperaciones_ult_12mpersonas_a_cargosituacion_vivienda_ALQUILERsituacion_vivienda_HIPOTECAsituacion_vivienda_OTROSsituacion_vivienda_PROPIAobjetivo_credito_EDUCACIÓNobjetivo_credito_INVERSIONESobjetivo_credito_MEJORAS_HOGARobjetivo_credito_PAGO_DEUDASobjetivo_credito_PERSONALobjetivo_credito_SALUDfalta_pago_Nfalta_pago_Yestado_civil_CASADOestado_civil_DESCONOCIDOestado_civil_DIVORCIADOestado_civil_SOLTEROestado_cliente_ACTIVOestado_cliente_PASIVOgenero_Fgenero_Mnivel_educativo_DESCONOCIDOnivel_educativo_POSGRADO_COMPLETOnivel_educativo_POSGRADO_INCOMPLETOnivel_educativo_SECUNDARIO_COMPLETOnivel_educativo_UNIVERSITARIO_COMPLETOnivel_educativo_UNIVERSITARIO_INCOMPLETO
1009822900034.0650000.149.63034.015577.013940.0114.01.0FalseTrueFalseFalseTrueFalseFalseFalseFalseFalseTrueFalseFalseFalseFalseTrueTrueFalseFalseTrueFalseFalseFalseTrueFalseFalse
1009925950024.0610000.167.51050.014596.03688.0120.01.0TrueFalseFalseFalseFalseTrueFalseFalseFalseFalseTrueFalseFalseFalseFalseTrueTrueFalseTrueFalseFalseFalseFalseFalseTrueFalse
1010025950032.0680000.147.14040.015476.04003.0117.02.0TrueFalseFalseFalseFalseFalseFalseTrueFalseFalseTrueFalseFalseFalseFalseTrueTrueFalseFalseTrueFalseFalseFalseFalseTrueFalse
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